- AutoEval won the Best Paper Award at RSS 2025 Robot Evaluation Workshop.
- Published a paper on how to do RL fine-tuning without offline data retention, Warm-start RL (WSRL), accepted at ICLR 2025.
- Led the first big project in his Ph.D., SOAR, which will be presented at CoRL 2024 in Munich.
- Will present undergraduate work, Tiered Reward: Designing Rewards for Specification and Fast Learning of Desired Behavior, at the RL Conference.
- Completed undergraduate thesis, Policy Transfer in Lifelong Reinforcement Learning through Learning Generalizing Features.
Research Experience
- Research intern at Physical Intelligence for the summer.
Education
- Currently a 3rd year CS Ph.D. student at UC Berkeley, advised by Professor Sergey Levine.
- Graduated magna cum laude from Brown University with an Sc.B. in Applied Math and Computer Science, where he was advised by Professors George Konidaris and Michael Littman.
Background
Research Interests: Reinforcement learning, building autonomous generalist robots.
Miscellany
Personal Interests: Playing guitar, cooking, playing badminton, watching standups and movies.